Due to increasing global population, salt marshes have been subjected to multiple stressors such as increasing nutrient loadings and historical contamination. In order to better understand how does the salt marsh plants auto-remediation capacity (phytoaccumulation of metals) is affected by cultural eutrophication, an experiment was performed under controlled conditions. Plants were exposure to equal metal concentrations (Zn, Cu, and Ni – micronutrients, and Cd – class B metal) simulating historical contamination and three different concentrations of nitrogen (nitrate) simulating steps of cultural eutrophication. According to our study, under the tested concentrations, cultural eutrophication does not seem to affect Zn, Cu and Ni phytoremediation of H. portulacoides, but the ecosystem service of Cd phytoremediation seems to be promoted. Nevertheless, Cd high toxicity and bioaccumulation should be taken into account, as well as the vulnerability of salt marsh ecosystems, whose reduction will have drastic consequences to the ecosystem health.

Due to increasing global population, salt marshes have been subjected to multiple stressors such as increasing nutrient loadings and historical contamination. In order to better understand how does the salt marsh plants auto-remediation capacity (phytoaccumulation of metals) is affected by cultural eutrophication, an experiment was performed under controlled conditions. Plants were exposure to equal metal concentrations (Zn, Cu, and Ni – micronutrients, and Cd – class B metal) simulating historical contamination and three different concentrations of nitrogen (nitrate) simulating steps of cultural eutrophication. According to our study, under the tested concentrations, cultural eutrophication does not seem to affect Zn, Cu and Ni phytoremediation of H. portulacoides, but the ecosystem service of Cd phytoremediation seems to be promoted. Nevertheless, Cd high toxicity and bioaccumulation should be taken into account, as well as the vulnerability of salt marsh ecosystems, whose reduction will have drastic consequences to the ecosystem health.

Platinum contamination in estuarine and coastal sediments has been evaluated in three cores collected from the Tagus Estuary and Prodelta shelf sediments. Elevated concentrations, up to 25-fold enrichment compared to background values, were found in the upper layers of the estuarine sediments. The degree of Pt enrichment in the estuarine sediments varied depending on the proximity to vehicular traffic sources, with a maximum concentration of 9.5ngg⁻¹. A considerable decrease of Pt concentrations with depth indicated the absence of significant contamination before the introduction of catalytic converters in automobiles. Platinum distribution in the Tagus Prodelta shelf sediment core showed no surface enrichment; instead a sub-surface maximum at the base of the mixed layer suggested the possibility of post-depositional mobility, thereby blurring the traffic-borne contamination signature in coastal sediments.

Platinum contamination in estuarine and coastal sediments has been evaluated in three cores collected from the Tagus Estuary and Prodelta shelf sediments. Elevated concentrations, up to 25-fold enrichment compared to background values, were found in the upper layers of the estuarine sediments. The degree of Pt enrichment in the estuarine sediments varied depending on the proximity to vehicular traffic sources, with a maximum concentration of 9.5 ng g−1. A considerable decrease of Pt concentrations with depth indicated the absence of significant contamination before the introduction of catalytic converters in automobiles. Platinum distribution in the Tagus Prodelta shelf sediment core showed no surface enrichment; instead a sub-surface maximum at the base of the mixed layer suggested the possibility of post-depositional mobility, thereby blurring the traffic-borne contamination signature in coastal sediments. | This work was partially supported by a P.I. project (ref. 200830I150) granted to A.C.G. from the Spanish Ministry of Science and Innovation. INGMAR project funded the PALEO1 cruise where Prodelta sediment core was collected and FCT project TAGUSED (POCTI/2001/CTA/41411) financed the analytical work on this core. | Peer reviewed

Phytoplankton diversity, primary and bacterial production, nutrients and metallic contaminants were measured during the wet season (July) and dry season (March) in the Bach Dang Estuary, a sub-estuary of the Red River system, Northern Vietnam. Using canonical correspondence analysis we show that phytoplankton community structure is potentially influenced by both organometallic species (Hg and Sn) and inorganic metal (Hg) concentrations. During March, dissolved methylmercury and inorganic mercury were important factors for determining phytoplankton community composition at most of the stations. In contrast, during July, low salinity phytoplankton community composition was associated with particulate methylmercury concentrations, whereas phytoplankton community composition in the higher salinity stations was more related to dissolved inorganic mercury and dissolved mono and tributyltin concentrations. These results highlight the importance of taking into account factors other than light and nutrients, such as eco-toxic heavy metals, in understanding phytoplankton diversity and activity in estuarine ecosystems.

International audience | Phytoplankton diversity, primary and bacterial production, nutrients and metallic contaminants were measured during the wet season (July) and dry season (March) in the Bach Dang Estuary, a sub-estuary of the Red River system, Northern Vietnam. Using canonical correspondence analysis we show that phytoplankton community structure is potentially influenced by both organometallic species (Hg and Sn) and inorganic metal (Hg) concentrations. During March, dissolved methylmercury and inorganic mercury were important factors for determining phytoplankton community composition at most of the stations. In contrast, during July, low salinity phytoplankton community composition was associated with particulate methylmercury concentrations, whereas phytoplankton community composition in the higher salinity stations was more related to dissolved inorganic mercury and dissolved mono and tributyltin concentrations. These results highlight the importance of taking into account factors other than light and nutrients, such as eco-toxic heavy metals, in understanding phytoplankton diversity and activity in estuarine ecosystems.

Combining GIS with neuro-fuzzy modeling has the advantage that expert scientific knowledge in coastal aquaculture activities can be incorporated into a geospatial model to classify areas particularly vulnerable to pollutants. Data on the physical environment and its suitability for aquaculture in an Irish fjard, which is host to a number of different aquaculture activities, were derived from a three-dimensional hydrodynamic and GIS models. Subsequent incorporation into environmental vulnerability models, based on neuro-fuzzy techniques, highlighted localities particularly vulnerable to aquaculture development. The models produced an overall classification accuracy of 85.71%, with a Kappa coefficient of agreement of 81%, and were sensitive to different input parameters. A statistical comparison between vulnerability scores and nitrogen concentrations in sediment associated with salmon cages showed good correlation. Neuro-fuzzy techniques within GIS modeling classify vulnerability of coastal regions appropriately and have a role in policy decisions for aquaculture site selection.

Combining GIS with neuro-fuzzy modeling has the advantage that expert scientific knowledge in coastal aquaculture activities can be incorporated into a geospatial model to classify areas particularly vulnerable to pollutants. Data on the physical environment and its suitability for aquaculture in an Irish fjard, which is host to a number of different aquaculture activities, were derived from a three-dimensional hydrodynamic and GIS models. Subsequent incorporation into environmental vulnerability models, based on neuro-fuzzy techniques, highlighted localities particularly vulnerable to aquaculture development. The models produced an overall classification accuracy of 85.71%, with a Kappa coefficient of agreement of 81%, and were sensitive to different input parameters. A statistical comparison between vulnerability scores and nitrogen concentrations in sediment associated with salmon cages showed good correlation. Neuro-fuzzy techniques within GIS modeling classify vulnerability of coastal regions appropriately and have a role in policy decisions for aquaculture site selection.